TBNAI
I need context window
Publication: top scoring links : multi
Author: /u/Dapper_Chance_2484
Source published: 13/11/2026, 14:33:55 UTC
Briefing created: 14/11/2026, 01:22:18 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 14/11/2026, 00:47:25 UTC.
Briefings
A user reports a local LLM rig running Qwen 3.8 27B with 104k context, experiencing severe slowness and single-threaded execution despite hardware upgrades. The user plans to implement an agent orchestrator with sub-agents and tests, but the current setup takes over 24 hours to start tasks. The evidence indicates the rig is currently running at approximately 90 tokens per second (TPS) with 2x 3090 GPUs, while the 5090 rig is idle. No specific outcomes from the planned agent implementation are reported in the source.
Key points
- A local LLM rig running Qwen 3.8 27B with 104k context window is taking over 24 hours to start tasks.
- The rig is currently running at approximately 90 tokens per second (TPS) with 2x 3090 GPUs.
Context
This finding addresses a common bottleneck in local LLM deployment where hardware upgrades do not immediately resolve performance issues, specifically regarding startup latency and concurrency. The user's proposed solution involves an agent orchestrator with sub-agents and entry/exit criteria, which is a standard approach for managing local AI workflows.
Limitations
The evidence is a single user report from a Reddit thread. No specific dates for the proposed agent implementation are provided, and no quantitative results from the tests are included. The source does not specify the exact hardware configuration of the 5090 rig or the specific results of the planned agent implementation.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 14/11/2026, 01:22:18 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
View archived briefing on IPFS
bafybeidixeqzxjvintbwjwnea527zgp3pcuiqcjnp322clodrc4dchykya